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Optimal Monotone Mean-Variance Problem in a Catastrophe Insurance Model

Author

Listed:
  • Bohan Li

    (Soochow University)

  • Junyi Guo

    (Nankai University)

  • Xiaoqing Liang

    (Hebei University of Technology)

Abstract

This paper explores an optimal investment and reinsurance problem involving both ordinary and catastrophe insurance businesses. The catastrophic events are modeled as following a compound Poisson process, impacting the ordinary insurance business. The claim intensity for the ordinary insurance business is described using a Cox process with a shot-noise intensity, the jump of which is proportional to the size of the catastrophe event. This intensity increases when a catastrophe occurs and then decays over time. The insurer’s objective is to maximize their terminal wealth under the Monotone Mean-Variance (MMV) criterion. In contrast to the classical Mean-Variance (MV) criterion, the MMV criterion is monotonic across its entire domain, aligning better with fundamental economic principles. We first formulate the original MMV optimization problem as an auxiliary zero-sum game. Through solving the Hamilton-Jacobi-Bellman-Isaacs (HJBI) equation, explicit forms of the value function and optimal strategies are obtained. Additionally, we provide the efficient frontier within the MMV criterion. Several numerical examples are presented to demonstrate the practical implications of the results.

Suggested Citation

  • Bohan Li & Junyi Guo & Xiaoqing Liang, 2025. "Optimal Monotone Mean-Variance Problem in a Catastrophe Insurance Model," Methodology and Computing in Applied Probability, Springer, vol. 27(1), pages 1-37, March.
    • Handle: RePEc:spr:metcap:v:27:y:2025:i:1:d:10.1007_s11009-024-10134-6
    DOI: 10.1007/s11009-024-10134-6
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    References listed on IDEAS

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